Evidence map›Paper›PMID 30683153›Full record

ArticleBMC research notes2019

Multivariate analysis of genomic variables, effective population size, and mutation rate.

Punit Bhattachan, Bo Dong

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Punit BhattachanKey Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, No. 5 Yushan Road, Qingdao, 266003, China.
Bo DongKey Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, No. 5 Yushan Road, Qingdao, 266003, China. bodong@ouc.edu.cn.ORCID http://orcid.org/0000-0003-1616-5363
Ocean University of China · CNQingdao National Laboratory for Marine Science and Technology · CN

Funding

the National Key Research and Development Program of China 2018YFD0900705
6 · The paper itself

Abstract

objectiveThe relationship between genomic variables (genome size, gene number, intron size, and intron number) and evolutionary forces has two implications. First, they help to unravel the mechanism underlying genome evolution. Second, they provide a solution to the debate over discrepancy between genome size variation and organismal complexity. Previously, a clear correlation between genomic variables and effective population size and mutation rate (Neu) led to an important hypothesis to consider random genetic drift as a major evolutionary force during evolution of genome size and complexity. But recent reports also support natural selection as the leading evolutionary force. As such, the debate remains unresolved.

resultsHere, we used a multivariate method to explore the relationship between genomic variables and Neu in order to understand the evolution of genome. Previously reported patterns between genomic variables and Neu were not observed in our multivariate study. We found only one association between intron number and Neu, but no relationships were observed between genome size, intron size, gene number, and Neu, suggesting that Neu of the organisms solely does not influence genome evolution. We, therefore, concluded that Neu influences intron evolution, while it may not be the only force that provides mechanistic insights into genome evolution and complexity.

Indexed as

Genetics, PopulationMutation RatePopulation DensityAnimalsDatasets as TopicGenetic DriftGenomeGenome SizeGenomicsHumansIntronsMultivariate AnalysisGenetic driftGenome evolutionGenomic variablesMultivariate analysis

Identifiers

PMID30683153
PMCPMC6347809
OpenAlexW2922254612

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.